As is known, in a weaving process a textile machine, e.g., a knitting machine, receives a plurality of yarns from respective feeders.
The yarn consumed in order to make the individual garments can be constantly monitored for the purpose of stopping the machine when the consumption deviates too far from a reference value, with consequent sizing errors.
The reference value is usually calculated by way of a preliminary learning procedure, during which a sample garment that conforms to the specifications is produced.
For some applications that are intrinsically less subject to sizing errors (e.g., the production of socks by way of small-diameter circular machines), the control system of the consumption of yarn can still be used to detect any anomalies that involve very small variations in consumption, such as the breakage of the needles of the machine.
It has in fact been found in practice that, by setting the intervention threshold to very low percentage values (in the order of 0.3-1% variation in consumption), the system is capable of detecting the breakage of even a single needle.
A drawback of this system for detecting anomalies is that, as is known, the measurement of the consumption of yarn is intrinsically subject to drift slowly over a period of hours (e.g., variations of 0.1 per thousand every hour), with consequent stoppages due to “false alarms” after a few hours of operation. In order to prevent such unjustified stoppages, it is therefore necessary to periodically stop the plant and repeat the learning procedure, at the expense of productivity.